Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Neural Circuits

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

IL-6-JAK2-STAT3 Signaling Pathway and the Pathogenesis of Chronic Tonsillitis.

Journal of interferon & cytokine research : the official journal of the International Society for Interferon and Cytokine Research·2026

Same author

Observation of localization reversal and harmonic generation in nonlinear non-Hermitian skin effect.

Nature communications·2026

Same author

Creation of a computational space with model-free metasurface neural network.

Nature communications·2026

Same author

The Weston Score in coronary artery calcification among patients with End-Stage Renal Disease.

Journal of cardiothoracic surgery·2026

Same author

Gauge-field-induced duality group in metamaterials.

Nature communications·2026

Same author

Dictated cell adhesion and migration using microfluidic-controlled synthetic hydrogels exhibiting programmable viscoelasticities.

Journal of materials chemistry. B·2026

Search research articles

Related Experiment Video

Updated: Sep 10, 2025

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

Published on: April 15, 2015

Nonreciprocal surface plasmonic neural network for decoupled bidirectional analogue computing.

Xiaomeng Li^1,2, Haochen Yang^1,2, Enzong Wu^1,2

¹International Joint Innovation Center, Zhejiang Key Laboratory of Intelligent Electromagnetic Control and Advanced Electronic Integration, Zhejiang University, Haining, China.

Nature Communications

|August 19, 2025

Summary

This summary is machine-generated.

Researchers developed a nonreciprocal optical neural network using spoof surface plasmon polaritons. This breakthrough decouples forward and backward paths, enabling independent bidirectional algorithms for advanced artificial intelligence computing.

More Related Videos

Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions

Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions

Published on: June 7, 2024

Evaluating Plasmonic Transport in Current-carrying Silver Nanowires

Evaluating Plasmonic Transport in Current-carrying Silver Nanowires

Published on: December 11, 2013

Related Experiment Videos

Last Updated: Sep 10, 2025

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

Published on: April 15, 2015

Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions

Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions

Published on: June 7, 2024

Evaluating Plasmonic Transport in Current-carrying Silver Nanowires

Evaluating Plasmonic Transport in Current-carrying Silver Nanowires

Published on: December 11, 2013

Area of Science:

Photonics
Artificial Intelligence
Materials Science

Background:

Optical neural networks offer high speed and low power for AI, but reciprocal designs couple forward and backward signal paths.
This coupling limits the exploration of backward pathways, hindering integrated perception-response systems.
Existing optical networks lack independent control over signal directionality.

Purpose of the Study:

To present a novel nonreciprocal neural network architecture.
To decouple forward and backward signal propagation in optical networks.
To enable flexible modulation of computing functions and independent bidirectional algorithms.

Main Methods:

Leveraging the enhanced magneto-optical effect in spoof surface plasmon polaritons transmission lines.
Utilizing ferrites for modulation of computing functions via magnetization orientation and operating frequency.
Demonstrating broadband bidirectional decoupled image processing and matrix-solving operations.

Main Results:

Successfully decoupled forward and backward paths in an optical neural network.
Achieved flexible modulation of network computing functions.
Demonstrated independent control and signal isolation within the same structure.
Emulated unidirectional transmission akin to biological networks.

Conclusions:

The developed nonreciprocal neural network enables independent control of bidirectional signal paths.
This architecture facilitates novel applications in analogue computing and integrated perception-response systems.
Opens pathways for nonreciprocal architectures in AI and signal processing.